Color bands make identifying individuals in the field possible without recapturing them
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A male from our Beaman Park site “Tailgate”

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# install.packages("ggsn")
state <- map_data("state")
county <- map_data("county")
beaman_point <- data.frame("x" = -86.905274, "y" = 36.269134)
rotary_point <- data.frame("x" = -87.271600, "y" = 36.501317)
cheatham_point <- data.frame("x" = -87.063088, "y" = 36.188858)
schiller_point <- data.frame("x" = -87.314360, "y" = 36.437066)

tn <- county %>% 
  filter(region=="tennessee")

davco <- county %>% 
  filter(region=="tennessee") %>% 
  filter(subregion=="davidson")

monco <- county %>% 
  filter(region=="tennessee") %>% 
  filter(subregion=="montgomery")

checo <- county %>% 
  filter(region=="tennessee") %>% 
  filter(subregion=="cheatham")

ggplot() + geom_polygon(data = state, aes(x=long, y = lat, group = group),
                        fill = "white", color="black") + 
           geom_polygon(data = tn, aes(x=long, y = lat, group = group),
                        fill = "gray", color="black") + 
           geom_polygon(data = davco, aes(x=long, y = lat, group = group),
                        fill = "yellow", color="black") + 
           geom_point(data = beaman_point, aes(x=x,y=y), color="navy") +
           geom_polygon(data = monco, aes(x=long, y = lat, group = group),
                        fill = "yellow", color="black") + 
           geom_point(data = schiller_point, aes(x=x,y=y), color="navy") + 
           geom_point(data = rotary_point, aes(x=x,y=y), color="navy") +
           geom_polygon(data = checo, aes(x=long, y = lat, group = group),
                        fill = "yellow", color="black") + 
           geom_point(data = cheatham_point, aes(x=x,y=y), color="navy") +
  coord_fixed(xlim = c(-90, -82.5),  ylim = c(34.8, 37), ratio = 1.2) + 
  xlab("Longitude") + ylab("Latitude") + ggtitle("LOWA Study Sites, TN")

Map of one of my study sites, located in the Cheatham Wildlife Management Area in Cheatham County, TN.

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lowaOGR <- readOGR("./data/Beaman2021.kml")
## OGR data source with driver: KML 
## Source: "/Users/JlaMacAir/Documents/r_docs/personal-website/data/Beaman2021.kml", layer: "beamanlowa2021.csv"
## with 6 features
## It has 2 fields
lowa2OGR <- readOGR("./data/Rotary2021.kml")
## OGR data source with driver: KML 
## Source: "/Users/JlaMacAir/Documents/r_docs/personal-website/data/Rotary2021.kml", layer: "rotary_lowa_2021.csv"
## with 3 features
## It has 2 fields
lowa3OGR <- readOGR("./data/Schiller2021.kml")
## OGR data source with driver: KML 
## Source: "/Users/JlaMacAir/Documents/r_docs/personal-website/data/Schiller2021.kml", layer: "schiller_lowa_2021.csv"
## with 3 features
## It has 2 fields
lowa4OGR <- readOGR("./data/Cheatham2021.kml")
## OGR data source with driver: KML 
## Source: "/Users/JlaMacAir/Documents/r_docs/personal-website/data/Cheatham2021.kml", layer: "cheatham_lowa_2021.csv"
## with 4 features
## It has 2 fields
A female from our Rotary Park site
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